Shows the attributes on critical thinking towards Teaching & Learning Activities & challenges.
\r\n\tIn this book the authors will provide complete introduction of Polymers chemistry. The book is mainly divided into three parts. The readers will learn about the basic introduction of general polymer chemistry in the first part of the book.
\r\n\tThe second part of the book starts with a chapter which includes kinetics of polymerization. Polymer weight determination, molecular weight distribution curve and determination of glass transition temperature. The final part of the book deals polymer degradation which includes types of degradation. The chapters of the present book consist of both tutorial and highly advanced material.
Active learning requires students to develop their understanding of content through the active construction of product, the solving of a problem or both embodies a long human tradition of learning through doing [1]. Active Learning refers to any strategy or activity where the responsibility of learning is placed on the learner and secondarily on instructor. It emphasizes learning, not teaching. In active learning strategy, students learn by directly engaging in the material they are studying through reading, writing, discussing etc. There is much research going on, educators have been talking over 30 years about active learning. In that process they have come up with a definition of active learning which is stated as an instructional method in which students actively participate in their learning process via learner-centered activities that exercise the higher order thinking skills of analysis, synthesis and evaluation rather than passively listening to a lecture. Instructors should know that the learner is a unique individual, variations in the culture and background of the learner. As the learner progresses he or she should take increasing responsibilities for his/her learning. Active leaning is a highly effective approach to teaching at the university level. Instructional strategies for active learning can take many forms, including writing, role-playing, gaming, constructing, experimenting, simulating, observing, and discussing. Active learning occurs when students participate in their own learning, no matter what specific activity is involved. Active learning is thinking made visible, with evidence of analysis, synthesis, and evaluation. It goes beyond passive listening, memorization, and recitation. The unique characteristics of digital technologies can enhance – intensify, increase, amplify – active learning. Open source software, web apps, common digital cameras, and almost ubiquitous mobile technologies empower and engage students as they construct, build, create, and distribute products that represent and reinforce their learning. These technologies provide opportunities for simulation, experimentation, research, and self-expression. In turn, social media exponentially improve access: access to information, to opportunities for collaboration, to alternative perspectives, and to audiences for student-generated products [2]. Flipped classroom technique has changed my perspective towards teaching and learning process. For the first time, I have come out of myself and watched my class from student point of view. Out of all teaching and learning techniques so far I come across, I feel Active Learning technique has found to be an effective method of teaching the course I am handling now to my students. In my previous years of teaching experience, I used to follow pedagogical approach by teaching detailed explanations about various concepts and dictate the important points to the students. After undergoing various training programs and attending various workshops on teaching engineering education such as the one I am undergoing now, I have realized that only advanced learner can understand my teaching abilities. Even an average learner will get bored and lose concentration and interest on my teaching. In order to bring maximum attentiveness and create interest in students and their learning, I should be able to adopt Active Learning technique to teach engineering course to group of students various cognitive levels. A visual and sequential style of teaching followed by creating an Active Learning environment in the classroom could help the students gain more knowledge and interest in learning. Flipped classroom technique can be adopted to teach some of the topics in Electromagnetic course such as Properties dielectric materials, Gaussian laws, Poisson Equations, Maxwell’s equations etc. While discussing about properties of dielectrics I can throw some questions for students by explaining some case studies. For example, while teaching a property of permeability such as density, relative density and surface boundaries. Also they can be asked to explain the phenomenon of capillary raise in tubes of very small diameters, non-mixing of some fluids such as oil and water etc. The topic of flow through pipes can be taught more interestingly by making them to conduct small experiments on branched pipes and how the discharge could be affected. I will also ask the students to divide into groups in order to allow each group to conduct a suitable experiment for understanding the concepts and phenomena and prepare a video on the experiment they will conduct. Also they can be asked to make a pipe with bends and small enlargements and contraction to estimate the loss of head due to various major and minor losses such as bends, sudden enlargement, sudden contraction, friction etc.
It is obvious that online teaching/learning is a proven successful technique to teach engineering education. Still there are some obstacles and hindrances in attaining effectiveness. This could be suitable platform for student community who has high degree of dedication and self-discipline. As it becomes difficult for the teacher to assess the state of level of understanding of the student, online courses are less efficient. Also there exists a lack of credibility and individuality in submitting the assignments. As a teacher we should be in a position to know the different learning styles of students present in the class based on the we have to change our teaching style, the implementation of different teaching styles in the classroom can help us to find way for success of all students. The way a teacher presents the lecture depends on the teacher’s preferences. The way a student learn does not always match with the teaching style of a teacher. Mismatches may happen and students become bored sometimes. The teacher finds difficulty in understanding the learning style of the students. In a conventional/traditional classroom the teacher can change learner’s style of learning if found not suitable immediately as per the response received from the students attending that class at that moment. But in case of an online teaching/learning, the teacher will require more time to assess the learning style of the students. This is the major challenge in any online course in my perspective. There were thirteen important tricks that will help students for effective learning as [3].
Motivate and relate new material to previous and future topics (Sequential, Global)
Provide balance of concrete information (sensing) and abstract concepts (intuitive).
Encourage all students to exercise both sensing and intuitive learning etc.
Encourage cooperative learning of home work.
Pause to allow time for reflection.
Use computer assisted instructions.
Plan active learning strategies suh as 5-minute brain storming.
Assign some drills for practice and some problems requiring analysis.
Encourage creative solutions.
Talk students about the learning styles, during advising in the class.
Use pictures, schematics graphs etc. before during and after verbal is shown.
Prove concrete examples described by theory.
Balance practical problem solving with fundamental understanding.
Concept on Critical thinking by the use of technology.
Faculty must poses to solve problem critically the first thing is reasoning, evaluating the data or any analytics, problem solving skills, decision making and analyzing this process can be done as individual work or a collaborative work/group work. The below Table 1 shows the relationship between critical thinking attributes, teaching/learning activities and challenges for critical thinking.
Critical Thinking Attributes | Teaching/Learning Activities | Challenges for Critical Thinking |
---|---|---|
Look for multiple answers, elucidations, opinions, options, solutions | Use multiple case studies, programs, examples that illustrate variation, comparison and connection | Examine students to generate multiple opinions, views, solutions, investigation in projects/assignments |
Evaluate assess concept, planning, methodology, solutions | Taking risk (by implementing various strategies to design an IOT project) | Give feedback (every day, every week) but the process to be continuous to make the students gets satisfaction of what they are doing |
Independent and creative thinking | Inductive teaching rather than deductive teaching | Provide students with necessary information and data or material for which they can identify the problem and give various solutions |
Shows the attributes on critical thinking towards Teaching & Learning Activities & challenges.
There are various strategies to think critically and most of this work may or may not be only individual role but can be seen in group course work/project work in collaborative manner.
Continuous discussion between faculty and students
Analyzing the problems through case studies and providing necessary solutions
Reading lecture material and referring to research articles from reputed journals
Use of software’s to trace and track problems wherever encountered in designing and building files
Summarizing the concepts gathered from the date of project given
Identifying the types of components to be used and to list the working principles of those components
Asking question between different groups and teams members
Resources/materials/data sheets to be used for the products
Enumerate the possible aspects of outputs and results
Instructors need to show some involvement when the students get stuck completely and making them to understand the situation and showing ways to rectify the problems in their projects for real time applications.
Online/offline mode of discussion between students-student’s interaction, faculty-student interaction etc.
Self-correctness for identify, analyzing and summarizing between theoretical and practical concepts.
Should poses the caliber to manage time using GNATT chart, PERT-1 chart, and PERT-2 chart or must take advice from guide or supervisor for time management between regular classes and project works (mini and major project).
Asking the Right Questions: Critical thinking is best supported when instructors use critical questioning techniques and demonstrating the live projects on IOT to engage students actively in the learning process.
Sample questions from all these studies include the following:
What do you think about this?
Why do you think that?
What is your knowledge based upon?
What does it imply and presuppose?
What explains it, connects to it, leads from it?
How are you viewing it?
Should it be viewed differently?
These questions require students to evaluate the clarity and accuracy of their thinking as well as the depth and breadth of their thinking. Have they considered all the alternatives? Do they know why they think the way they do? Students need to determine whether the content they are using is relevant and if their thinking process is logical. By questioning their thought process, students can begin thinking about their thinking. Research on questioning methodology also suggests that instructors should wait for student responses too often the students’ silence is filled by the instructor re-wording the question or asking a different student for a response. However, most students need at least 8 to 12 seconds to process and formulate their response, especially in critical thinking situations. If a question is based on rote memory recall, speed may be relevant; however, thinking requires time and patience. Give students the time they need to think critically [4].
The 21st century essential skills includes:
Personal and social responsibility
Planning, critical thinking, reasoning and creativity
Strong communication skills, both for interpersonal and presentation needs
Cross-cultural understanding
Visualizing and decision making
Knowing how and when to use technology and choosing the most appropriate tool for the task [5].
Active Learning.
The benefits of Active Learning are as follows:
Students are more likely to access their own prior knowledge, which is a key to learning.
Students are more likely to find personally meaningful problem solutions or interpretations.
Students receive more frequent and immediate feedback.
The need to produce forces learners to retrieve information from memory rather than simply recognizing a correct statement.
Students increase their self-confidence and self-reliance.
For most learners, it is more motivating to be active than passive.
A task that one has done himself/herself or as part of a group is more highly valued.
Student conceptions of knowledge change, which in turn has implications for cognitive development.
Students who work together on active learning tasks learn to work with other people of different backgrounds and attitudes.
Students learn strategies for learning itself by observing others [2].
The benefits of active learning are widely acclaimed in higher education. According to Guthrie and Carlin (2004), modern students are primarily active learners, and lecture courses may be increasingly out of touch with how students engage their world. Chickering and Gamson (1987) early proponents of active learning, designated “encourage active learning” as one of seven principles of good practice in higher education. Clickers offer one approach to employing active learning in the classroom. They are more formally denoted as Student Response Systems (SRS), Audience Response Systems (ARS), or Personal Response Systems (PRS) (Johnson, 2004). Clickers allow students to participate in classroom activities, regardless of class size and common student dynamics. These remote-like gadgets transmit individual student responses to an instructor’s computer to record and even share these results directly back to the class. Instructors can also use this data to customize their lessons for each learning group (Kenwright, 2009). Johnson (2004) describes how clickers address three of Chickering and Gamson’s (1987) seven principles for good practice in undergraduate education, as follows [2]:
Actively engage students during the entire class period.
Gauge their level of understanding of the material being presented.
Provide prompt feedback to student questions.
The article written by R. Felder and L Silverman is gave me a thoughtful idea on implementing different learning styles and then to relate it on teaching style.
As it basically happens with me that when I teach students hear me out but what’s the outcome of it students just make notes/clearing exams do they really obtain necessary knowledge which they can implement in their real time application and could they become that much confident in the ever changing competitive world. I teach a subject which is more practical oriented rather than theoretical and yes my learning style always influenced my teaching style. The mode of learning style which merely I adapt is Sensing Learning (Sensing Learners) though I acquire visual learning, active learning and I am more enthusiastic in blended learning by using CANVAS, MOOC (global leaning), because I see the devices and would like to work with devices but yes it takes time for me to implement, and to be clear to the point I explain them based on practical methodologies like how to make necessary connections, current calculation, parameter measurements and synthesis. A teacher should always be dynamic must poses interdisciplinary skills to share knowledge with different levels of students.
The course which I teach is Electrical Installation and Estimation which is highly practical oriented course which requires high understanding and problem solving skills to make this course interactive and engaging, I prepare some prototypes (devices) and take it to class room and display its working/principle functionalities to all different levels of students. I continuously adapt new teaching methodologies to felicitate lecture which becomes highly engaging with students they ask various questions. After taking the course, I have implemented many ways of learning and teaching styles. Each student has its own way of learning but what I believe and have observed is that.
Foremost thing what exactly we are teaching and what are the objectives of the concerned course that matters the most. At the end of the course what students ability is did they possess clear understanding of the topics, did they implemented any prototypes etc. There are different courses each course has its unique identity some contains theoretical, practical, problematic, application oriented.
In the reading there are various model show cased that improves the quality of teaching and learning style to be used when felicitating a lecture to the different levels of learning styles (different levels of students). The models which are reflective in the paper are
Jung-Myers-Briggs model
Learning style model
Teaching style model
Kolb’s model
As mentioned in the reading there are different types of learning styles and each learning style are sub divided into two types (Table 2).
Perception | Input Modalities | Organization | Processing | Understanding | |||||
---|---|---|---|---|---|---|---|---|---|
Sensory | Intuitive | Visual | Auditory | Inductive | Deductive | Active | Reflective | Sequential | Global |
Shows the different types of learning styles.
Each learning style has advantage and disadvantage, if a student is a sensory learner then he is keen observant, more practical oriented, relies on fact/concrete data, does work in effective manner but this learner will not be able to perform well as compare to intuitive learners they are fast but reckless, they grasp quick but no implementation etc. As per the R. Felder and L Silverman reading that each learning styles differs it also depends based on the ability and the type of exam they choose. In the organization based learning style there are two types inductive learning style is based on natural behavior of student but a deductive learning style reduces interest in learning in the field engineering. The major impacts of teacher on different learning styles are
Be organized: In one-hour session what teacher should do and how activity can be assigned so that each learning styles meets the required level of understanding (proper time management).
Pleasant: Always sound pleasant to students such that when they ask question they should not hesitate.
Sound knowledge: A teacher must pose technical and practical knowledge to address all the levels of students and to meet their pre-requisite standards.
Disciplined
Trustworthy
Honest
Sincere
Committed to teach: not by chance or choice; should have zeal and passion to teach all levels of learners.
Be present and available for students whenever they came to ask question or doubts
As per the R. Felder and L. Silverman, in engineering education there are students which have different learning abilities, different customs, rules/regulation but as a teacher we must follow new learning and teaching styles to address all the students effectively. As in a class room there are active learners or passive learners we should encourage all the students to majorly focus on objectives, content for the course which they are undertaking. As a teacher we need to be versatile, upto-date and dynamic since there are huge advancement in technologies day by day. This article was very helpful in finding ways of teaching by implementing new ways of learning in engineering education.
Technology plays an important role in making students more interactive, participative in classroom especially after the post lunch session where students feel drowsy in detail discussion on Technology enabled active learning is explained in [6]. As there is advancement in technology the demand of online learning courses increases over traditional class room courses. Due to flexibility in time, type of course, quality of education, completion of assignments etc.
The key aspects to remember in online courses over traditional class room courses are
Flexibility/Time management
Discipline
Blended education model
Social interaction
Organized lectures
Resources, materials and assignment on time
Online course requires dedication and interest to complete the course in a given amount of time. There are many misconceptions from student’s side that by skipping classes they can complete the course, completing the assignment one day before or two days before the deadlines.
Focus on quality of education in online course
Design of online course material
Schedule of online course
Course planning/Lesson plan
Time management
Assessment
Evaluation/Rubrics
Quizzes
Attendance
Interactive (Poll questions, clearing doubts)
In large online classes clearing doubts in one-hour session becomes difficult for faculty and when it comes to assessing student performance of more than 90 students becomes very arduous.
Time management is important factor to discuss cognitive issues in online courses.
Able to adapt different learning styles from the beginning
After going through an online course student will be able to develop own learning styles and self-learning abilities it also builds up confidence.
Sharing knowledge is highly encouraged in discussion forums among students and faculty which makes them to think in different learning levels.
For all different levels of students, it gives a clear platform to acquire required skills and knowledge by asking questions.
As most of the LMS or CMS is implemented and developed in US based education system which is highly resourceful and knowledgeable as expert faculties and advisors will be available to upgrade and enhance students learning also expert technical team will be available to tackle out the problems associated with E-Learning class room.
Online courses are organized in an effective way to provide quality education to students for upgrading their skills and knowledge.
No social communication with classmates
Limited time period to complete the course
The concept of active learning comes out of interest of students and making lectures interactive but when we conducting an active learning environment for the first time in class room students find it difficult in the beginning but when they are accustomed to it becomes simple and energetic, during the first class activity were all students are new to each other we can use can activity called ICE Breaker. Active learning among students recuperates the quality of education and also improves students’ performance in solving critical problems, retention of knowledge for longer period, motivation, confidence and better development in communication/interpersonal skills. It is a learner centered approach to teaching.
The major concerns in designing and implementing active learning in class are
Time management
Forming good groups/average groups
Organizing an activity with limited time period
For all different levels of students an active participation
Large size classroom
Material/complete handouts
Regularity/Punctuality of students
Disturbances (use of mobiles, ring tone, outside disturbance)
Strategies to overcome the major concerns (Table 3).
Time Management | It is an important factor to any cause. In one hour session how to manage the lecture, topic and an activity. I have chosen a 15 minutes group activity for design of circuit and to do basic calculations. What I have found is some students have completed the task in 8 minutes and remaining seven minutes for them got wasted. For other groups they took entire 15 minutes to complete the task but some groups not even completed. |
Forming good groups/ average groups | To know the level of understanding of each student I have conducted a pre-test to check everyone’s knowledge depending on that I have formed groups. |
Organizing an activity with limited time period | As said time is a major issue every second counts. We need to make sure that students get engaged in the task and try out new ways to solve critical problems even though the solution is not correct but trying is worth more than enough during this session. |
Active Participation | It is very important that every student participate in activity choose an activity which catches students attention if its difficult problem they will hesitate to do it. If the activity is short and simple for them to design then students can ask more question related to that topic. The activity which I have chosen was JIGSAW, Think-pair-share and one minute paper writing. |
Large size classroom | Not all the question of students will be covered in the activity but I have suggested students to pen down their question on a paper and submit to me so that the very next day I can able to answer all questions. I am presently using CANVAS for this task where students have asked me questions about their topics frequently. This becomes quite simple to answer all their queries in small amount of time. If the questions posted by students are thoughtful in that particular case I will discuss in class with all. |
Material/handouts | Basically students like spoon feeding, the more we feed them the more they crave for. In this area I have encouraged my students to make their own notes or do self-study by providing them with necessary links and materials. If the situation is very worse (average or weak students) then I personally provide them with proper material/handout to understand the subject and should be able to apply in real time application. This happened with me where I have provided students with proper material and they really have implemented their micro, mini and major projects which are highly applicable for any application. |
Regularity and Punctuality | Students can learn only if they are regular and punctual to their lectures. As the activity or the topic which we teach is thoughtful then the students will be regular/punctual. We should not repeat the same activity day by day as students feel that the teacher knows the area only apart from it does not know. Sometimes we must engage in learning with them and at times students really find some interest in attending classes/lectures. |
Disturbance | Now days as there is huge demand of technology if we bring into classroom it causes disturbance in teaching and for other learners. In my previous experience students are allowed to bring the mobile phones with them for every 5 to 10 minutes a ring will be there which causes huge disturbance for me and to the learners. But in my present experience here students deposit they mobile phone in college cellar and there is no such cause of disturbance. |
Shows the activities performed on various parameters.
Technology and Engineering Education is the use of accumulated knowledge to process resources to meet human needs to improve the quality of life. Students develop the ability to select and correctly use course materials, modern tools, techniques and processes to answer questions, understand explanations and solve problems encountered in real life applications in mini/major projects. These overriding themes require students to design, research, create, use, evaluate and modify systems of Electronics, Electrical, Biotechnologies, Information Technologies, Cyber Technologies and Physical Technologies [7] (Figures 1–15).
Shows the dashboard of LMS which includes various courses.
Shows the syllabus of EIE course.
Shows the notes uploaded for students reference and learning.
Shows the assignments/discussion given to students.
Shows the discussion question for 10 points.
Shows the students response for the given question.
Shows another student response for the given question.
Shows the assignment task.
Shows the assessment tool used rubrics.
Shows evaluating students’ performance using speed grader system.
Shows the attendance list of students and their activity details when using canvas (2019).
Shows the total strength of students list when available online & date.
Shows the attendance list of students & faculty and their activity details when using canvas (2019).
Shows the use of technology through Whatsapp54 6 for transferring the information on EEE course.
Shows the use of technology mentioned here is the four-year duration of course of syllabus (2017–2021) batch.
There are advantages and disadvantages of active learning in class room some students learn but some do not but I as a teacher it’s my responsibility to make them learn and concentrate in class. Active learning boosts the confidence of students and their involvement towards the subject.
Hence by implementing the above strategies student’s confidence has improved they discuss their ideas and thoughts without any hesitation. There were some difficulties in managing classroom due to sudden change of teaching from traditional method to active learning methodologies in the initial classes but later with more organized manner I was able to implement good strategies in classroom such as Think Pair Share, Write Pair Share, Collaborative learning, JIGSAW etc. and many more. Below statistical representation of data is shown and improvement of students leaning through active learning techniques [8] (Tables 4 and 5).
11 | 18 | 7 | 36 | |
8.33% | 80.55% | 11.11% | 100% |
Shows the performance of students.
Deepening the understanding of the concept | ✔ | — | — | — |
Promoting motivation to learn more about the concept/subject | — | ✔ | — | — |
Encouraging class participation | ✔ | — | — | — |
Building confidence | ✔ | |||
Contributing to the joy of learning | — | ✔ | — | — |
Shows the feedback obtained from students upon the conduction of activity based learning.
The major goal for engineering educators who want to instill critical thinking skills in their classrooms is to think of their students not as receivers of information, but as users of information. Learning environments that actively engage students in the investigation of information and the application of knowledge will promote students’ critical thinking skills. In engineering education any skill, critical thinking requires training, practice, and patience. Students may initially resist instructional questioning techniques if they previously have been required only to remember information and not think about what they know. They may struggle with assessment questions that are not taken precise from the book. However, by encouraging students throughout the process and modeling thinking behaviors, students’ critical thinking skills can improve [5]. The reasons for allowing new teaching & learning techniques in classroom is to enhance the ideology of students to learn new things and to develop a real time project to tackle day-to-day life challenges, engaging in group learning activities helps the students to communicate with their peers without any hesitation. The learning outcomes for any engineering subject allows them to think and to do self-learning where teacher acts as facilitator and students a learner.
The above activity through technology based learning was implemented for diploma EEE second year students in Electrical Installation and Estimation and for B.Tech CSE Third year students on Non-conventional Energy resource, has a common topic on Safety procedures in electrical power engineering (Table 6).
S.No. | Questions | Poor | Fair | Good | Excellent |
---|---|---|---|---|---|
1. | Clear to understand the course content | 0% | 10% | 20% | 20% |
2. | Discussions/materials posted was useful | 0% | 15% | 10% | 15% |
3. | Would you recommend this course to friends | 0% | 12% | 24% | 14% |
4. | Have you enjoyed online learning through technology based | 5% | 10% | 15% | 10% |
5. | How far the topic was relevant | 4% | 20% | 20% | 6% |
Shows the feedback obtained from students on electrical & electronics engineering course.
At the end of the conclusions the following issues the students face when using technology and solutions as per student’s feedback being provided below:
Limited social interaction
There is a limited opportunity to interact face to face to professors and other peers.
Difficulty to develop relationships with classmates.
Possibility of limited local networking opportunities.
Most of the communication through e-mail, chat room of discussion groups, but no office to get together.
No campus atmosphere to create social interaction.
Computer boot-up time, software, connection to internet student may be required to learn computer trouble shooting skills.
Addition cost of high speed internet.
Planning and adjust the studying schedule around instructor’s assignment due date. If a student is scheduling to study in the nights, then he/she will have to wait for response from instructor.
Students must have convenient access to the internet at home or through college, library and community computer.
Students must know exactly what kind of technological support they need for certain course and properly equip themselves for the successful completion of assignments.
To manage the assignments and course in an organized manner student need to develop proficiency in computer.
Students must learn basic knowledge of computers, internet and typing.
Students must have their own email accounts to access to a group conferencing program.
Students must demonstrate the maturity to be responsible in the use of internet and own email accounts.
Students must be self-motivated to get online and conduct their homework internet activities.
Students and faculty can communicate through discussion forums, discussions can help group work among students and sharing the knowledge which leads to higher learning outcomes.
Wind energy has been recognized as one of the fastest-growing energy sources in the world. The U.S. Energy Information Administration [1] reported that in 2020 the wind’s annual electricity generation exceeds 300 million MWh in the U.S., which surpassed the hydroelectric generation by 26 million MWh. In the last decade, the global cumulative wind power capacity installed has increased from about 200 gigawatts (GW) in 2010 to more than 650 GW in 2019, as shown in Figure 1 [2, 3]. Compared to 2018, the global wind power installed capacity in 2019 represents a percentage increase of 19% with a 10% increase in new installation, which is the second-largest increase in the last decade. This increase was the result of the largest market from China (237029 MW), EU-28 (192231 MW), the USA (105433 MW), and India (37529) [3, 4]. With the continuous technology development of renewable energy, wind power becomes predominant than hydroelectric, biomass, or geothermal energy [5]. Currently, in Europe alone, electricity generated from wind turbines covers up to 11% of the electricity demand; by 2020, it will increase to 16.5%, and by 2030 it is expected that renewable energy could serve at least 27% of Europe electricity need, and will generate over three million jobs. Globally, in 2020 the anticipated wind energy will be dominated by China (38%), Europe (28%), US (16%), and India (7%) and by 2030, based on central scenario, it is expected to have a cumulative installation of 323 GW in Europe alone. Governments, policymakers, and energy utility companies currently employ a wide array of tools to encourage the deployment of various renewable energy technologies including investments, funds, cash, and tax credits incentives.
Principle of the double multiple streamtube model.
Before the COVID-19 pandemic, the Global Wind Report published by the Global Wind Energy Council expected a record of new wind installed capacity of 76.7 GW in 2020 [3]. However, given the unpredictable effects of COVID-19 on various renewable energy sectors, it is expected that the wind energy market will generally be slowing down, as the current control of the virus in the US, Europe, and China is still difficult to predict [2]. The International Energy Agency [6], in its new report on the market update outlook for 2020 and 2021, forecasts a 12% decrease in wind power growth compared to 2019. Statista, the online portal for statistics, reported that the global wind market is expected to add 73 gigawatts only instead of the previous predicted installed capacity of 76.7 [7]. The downturn is primarily attributed to project delays instead of cancelations. Yet, there is still a steady increase in global wind installed capacity; for example, the U.S. added 1821 megawatts (MW) of new installed capacity during 2020 Q1 [1], and India added 0.2 GW during January–March 2020 [8]. The International Energy Agency forecasts that over half of Europe’s wind growth will come from the Netherlands, Germany, Sweden, Spain, and the U.K. There are currently up to 205 GW wind power installed capacity in Europe, representing 15% of EU-28 of the electricity consumed in 2019 [4].
With the growing ambition and enthusiasm on using the power of the wind to generate clean energy, added to the increasing investments and the drop in wind turbine pricing, more fundamental research and exploration is needed in the design of such wind turbine machines, including environment, social, and economic aspects of meeting the future functionality of large-scale deployment in both onshore and offshore areas. The present study aims to tackle one of the major problems that the wind turbine research community is concerned with [9, 10] by focusing on the aerodynamic loads and performance of vertical and horizontal performance wind turbines (VAWT & HAWT). The study provides a thorough mathematical and physics modeling of VAWT and HAWT aerodynamics using the Double-Multiple-Stream tube model (DMS) and blade element momentum theory (BEM) [11, 12].
In the last few years, significant research activities have been devoted to designing large-scale wind turbines with high hub height and large rotor diameter, making wind turbines the world’s largest rotating machines. Wind turbine rotor diameters were in the range of 5 to 15 m during the 1980s, with an average capacity of 30 kilowatts. In the early 1990s, the wind turbine installed power reached 500 kW with a rotor diameter of 30 m. In 2000, the wind turbine installed power reached 1.0 MW with a rotor diameter of 50 m [13]. Since then, the size of wind turbines is getting larger and larger; in 2018, the power capacity increased to 2.6 MW with a diameter of 110 m, many wind farms have rotor diameters of up to 120 m 5-MW installed power. Current wind turbine technologies and advances in aerodynamics and structural analysis produce lighter and larger wind turbine machines with increased annual energy production [14]. Modern wind turbines may now reach 164 m of the rotor diameter and a power rating of 9.5 MW, such as the Vestas V164–9.5 MW. According to Statista [15], by 2021, the state-of-the-art wind turbine’s rotor diameter is estimated to reach 220 meters. Recently, General Electric revealed the Haliade-X, the largest prototype ever designed by the company for a new offshore wind turbine and the most powerful wind turbine machine operating at a 13 MW power output and a rotor diameter of 220 m [16].
With the growing development of wind turbines on a large scale and the increasing amount of wind electricity generated, the current wind energy market needs to be a more competitive, cost-effective, and reliable renewable energy source. The International Renewable Energy Agency (IRENA) [13] reported several programs, projects, and research been introduced to investigate the development of such wind turbine machines and stimulate their commercial growth. The plans include innovation in rotor blade design and materials, optimization of power electronics, incorporating smart/intelligent wind turbines, and using recycling of materials the vast amount of materials used in the wind energy sector.
A long-term strategy to address the scientific and current wind turbine technology has been initiated by the European Academy of Wind Energy (EAWE) in 2016 [10]. The goal was to study and analyze the main barriers and priorities and promote cooperation among researchers in fundamental and applied sciences of wind turbines as more fundamental research and exploration are needed to design such large wind turbines. The EAWE presented and discussed 11 research challenges in wind energy development, namely the materials and structures, the wind and turbulence, the Aerodynamics of wind turbines, the control and system identification, the electricity conversion, the reliability and uncertainty modeling, the design methods, the hydrodynamics, the soil characteristics and floating turbines, the offshore environmental aspects, the wind energy in the electric power system, and the societal and economic factors of wind energy. Three years later, in the United States, the wind energy researchers [9] from the US Department of Energy at the National Renewable Energy Laboratory (NREL) invited the scientific community to interdisciplinary collaboration to tackle three significant wind energy challenges to transform wind engineering into one of the significant global low-cost power generation sources. The first grand challenge is to improve the understanding of the physics behind the wind resource and atmospheric flow in the critical region where the wind machine operates, the second big challenge is to tackle the corresponding structural and dynamics of large-scale rotating wind turbine machines, and the third grand challenge is the enhancement of energy capture, control, network stability, grid integration, optimization, and reliability. Nevertheless, to stay competitive, the cost of electricity generated from wind turbines must continue to decline.
Up to 75% of the overall costs of wind turbine energy production are attributed to upfront costs. In terms of the wind turbine machine’s performance and cost, rotor blades are considered the most significant wind turbine parts. The aerodynamic design and optimum shape of the rotor blades, with a high lift to drag ratio, directly impact the wind turbine performance and power generated. There are currently two types of modern wind turbine design: the Horizontal Axis Wind Turbine (HAWT) as the traditional wind pump, and the Vertical Axis Wind Turbine (VAWT) as the Darrieus design model. In both cases, the wind kinetic energy is extracted by the turbine’s blades and transformed into electrical power. Both wind turbine machines are currently used offshore and onshore to generate electricity. Although the HAWT is widely used, the VAWT offers a promising alternative due to its mechanical and structural simplicity of harnessing wind energy, scaling down, safety and accepting wind flow from any direction. However, this simplicity encounters a significant challenge during the simulation and computation of the aerodynamic loads. Indeed, during each rotation, the rotor blades encounter the wake it generated, in addition to the wake generated by the rest of the blades, and operate in a dynamic stall regime [11, 17]. Adding to this is the fluctuating nature of the loads due to wind turbulence affecting the wind turbine’s planned service life and the power generated, as reported in [18, 19].
Many aerodynamic models for predicting the forces and the power generated by a wind turbine have been developed. A complete state-of-the-art review, including the appropriate references, is given by [17, 20, 21, 22, 23, 24, 25]. The wind turbine loads analysis can be achieved using three effective methods: the momentum method through Blade Element Momentum (BEM), the vortex theory, and the Computational Fluid Dynamics (CFD) method, and more recently using artificial intelligence (AI) to predict wind speed and power performance [26]. With the increased development and installation of wind turbines as wind farms, more work has been investigated in the wake velocity deficits generated by the upfront wind turbines. It has been reported that in a full-wake condition the wind turbine power loss may reach up to 40% [23]. The main objective of all the aerodynamic models is to first determine the induced velocity field generated in the upwind and downwind of the rotor blade where the flow through the wind turbine is considered to be subdivided into several streamtube. Then, the lift and drag coefficient as a function of the incidence angle needed to determine the normal, tangential forces as a function of the azimuth angle and, finally, the torque and the generated power. It is important here to note that the wind turbine performance is affected by many parameters such as wind speed, tip-speed ratio (TSR), airfoil shape and size, turbine aspect ratio (H/R), the solidity of the rotor, the swept area, the rotational speed, and other parameters such as dynamic stall effects, the presence of spoilers. Wind turbine aerodynamic loads and performance predictions in the vortex methods use lifting lines or surface to represent rotor blade trailing and shed vorticity in the wake then; the induced velocity is then determined at any point using the Biot-Savard law [21, 26]. Two types of vortex models have been used in this approach: the fixed-wake and the free-wake models. These vortex models need a significant amount of computer time to predict the aerodynamic loads and performance of the wind turbine machine more accurately than momentum models.
In the models using Navier–Stokes equations such as the case in a steady incompressible laminar flow using finite volume method based on the widely known “SIMPLER” algorithm [27], such models are well suited for wind farms as it can compute the flow velocity everywhere in the rotational plane of the wind turbine machine as well as in its vicinity. In a comparative study conducted by Perić et al. [28] using Blade Element Method and CFD on two types of wind turbines, the DTU 10 MW RWT (Denmark Technical University 10 MW Reference Wind Turbine) blade and the MEXICO blade (Model Rotor Experiments In Controlled Conditions), the authors predict the aerodynamic performance of with an accuracy of 15% accuracy for the 10 MW RWT blade and 6% accuracy for the MEXICO blade experiment data. The author recognizes the CFD’s power to provide higher accuracy compared to the BEM or vortex methods. While the BEM was limited to wind speeds of 10 to 12 m/s, the CFD method with
In the Double, Multiple Streamtube models (DMS) developed initially been by Paraschivoiu [11, 29], the variation in the upwind and downwind induced velocities as a function of the azimuthal angle has been included. In this case, the wind turbine blade is divided into several elements assuming no interaction between the components. This method’s main principle is to determine the axial and angular induction factors using an iteration method. Then, the forces and power generated are defined in a similar manner to the VAWT. Figure 1 shows the double streamtube model principle where the machine is represented by a pair of actuator disks in tandem in the upwind and downwind zone, CARDAAV Code. The induced velocity decreases in the axial direction so that the downwind induced velocity is smaller than the upwind zone. With
The atmospheric wind shear in Eq. (5) is based on the Frost
The relative velocity and the local angle of attack in the upstream zone where the azimuth angle varies between
where
Using the same modeling above for the upwind region, the downwind area can also be calculated with the azimuth angle between
where the lift and drag coefficients
where
VAWT model: (a) integration points, (b) DMS model.
where
Finally, the power generated due to the lift and the losses due to the drag is given by
The impact of atmospheric wind turbulence on a wind turbine’s aerodynamic loads can be included in the DMS model using a stochastic atmospheric wind. The induced velocities necessary for predicting the forces were computed for each Streamtube in both the upwind and downwind zones of the rotor, including the longitudinal and lateral fluctuation velocities resulting from the fluctuating atmospheric wind. A wind time series in the rotor’s upwind zone is created to produce the turbulent wind velocity. Using a time delay in the time series based on a linear variation, the turbulent wind speed in the downwind zone is generated [11]. The total velocity of the fluctuating atmospheric wind is a superposition of a mean part and a stochastic fluctuating part. The values of the fluctuations velocities are performed by using the Fast Fourier Transform. The time series are assumed to propagate downstream of the rotor with the speed of the airflow disturbed by the presence of the wind turbine. The simulation uses Double-Multiple Streamtube model (DMS) with up to 1512 stream tubes for the whole Darrieus rotor (21 vertical stream tubes and 72 lateral stream tubes at every five degrees [11]. In the presence of atmospheric turbulence, the relative velocity and the local angle of attack are given by [18]:
where
Based on the Blade Element Momentum (BEM) method for the performance prediction of horizontal axis wind turbines (HAWT) and the Double Multiple Streamtube (DMS) method for the performance prediction of vertical axis wind turbine (VAWT), QBlade is an open-source used for wind turbine simulation and distributed under the General Public License with (GPL) free access [31, 32, 33]. The code includes extensive post-processing functionality for the rotor and wind turbine simulations, including different rotor blades and variables. The main modules of the QBlade computer code are given in Table 1 [32]; the modules include the airfoil design, the viscous-inviscid coupled panel method XFOIL analysis, the airfoil polar extrapolation above the stall point, the HAWT and VAWT rotor blade design, the BEM simulation, the structural blade design and analysis, the simulation, and the turbulent wind field generator.
QBlade objects structure and modules.
The theoretical formulation in QBlade is based on BEM and DMS. The rotor blade is discretized into a finite number of blade elements with defined cross-sections according to the radial position, profile, chord, twist, and length. Using the momentum theory, each blade section’s relative wind speed is computed, which is then used to calculate the angle of attack and the Determination of the airfoil lift and drag coefficients. Once these parameters are known, the aerodynamic normal and tangential forces are computed, then the thrust and torque of an element are determined. Similar to CARDAAV code, in QBlade, the iteration variables of the BEM method are the two induction factors, axial
Angles, velocity components, and forces acting on the HAWT rotor blade section.
Based on Figure 3, the inflow angle
Using the momentum and BEM theory and the solidity
where the normal and tangential force coefficients of the blade section are given by
The iteration technique used in the above equations is first to initialize the axial and radial induction factor
Flowchart of the iterative algorithm used in QBlade.
The computer code CARDAAV can evaluate several rotor shapes with a straight or curved blade and use a defined shape such as a parabola, catenary, or modified troposkien. The code also can include the so-called “secondary” Effects,” such as the rotating tower, strut, and the spoiler. Another involved and unsteady phenomenon due to airfoil undergoing large and rapid variations of the angle of attack with time is the dynamic stall. During the rotor’s rotation, the drag and lift coefficients present a different hysteresis than the case of static behavior. A dynamic delay of the stall to angles is substantially beyond the static stall angle, including massive recirculating regions moving downstream over the airfoil surface. In the case of VAWT, when the operational speed approaches its maximum, all the rotor blade sections go beyond the critical static stall angle of attack, the angle of attack changes substantially, and the entire blade operates under dynamic stall conditions, which will increase the unsteady blade loads and the wind machine structural fatigue. Different dynamic stall models with some modifications derived from static and dynamic airfoil tests have been incorporated into the CARDAAV computer code, such as the Gormont model and the indicial model [11, 34, 35]. Comparisons between aerodynamic performance predictions using dynamic-stall models show that the models provide a better prediction of the dynamic-stall regime characterized by a plateau oscillating near the experimental data of the rotor power function of wind speed [11].
This section presents a selection of results obtained by performing aerodynamic loads and performance prediction using CARDAAV, different variants, and QBlade computer codes, including dynamic stall. Results were achieved on Sandia 17-m and 34 wind turbine machine [36] and compared to available experimental data. CARDAAV is the original code using an ambient constant ambient atmospheric wind speed, while CARDAAS code incorporated a stochastic wind to account for the atmospheric turbulence. Both CARDAAV and CARDAAS are based on DMS methods.
Normal force coefficient as a function of azimuthal angle for 17-m wind turbine machine at TSR = 2.86.
The viscous code 3DVF uses numerical methods to simulate the flow field of VAWTs in cylindrical coordinates based on the solution of steady, incompressible, and laminar Navier–Stokes equations. Different dynamic stall models have been incorporated into the aerodynamic codes, namely the original Gormont model, the indicial model, and the MIT model [11, 34, 37]. Figure 5 compares the normal force coefficient’s distribution as a function of azimuthal angle for 17-m wind turbine machine at TSR = 2.86 using CARDAAS and 3DVF codes and experimental data. Using CARDAAS with low turbulence intensity induces a low variation in the ensemble-averaged values compared to the high turbulence intensity; obviously, for 0 turbulence intensity, both CRDAAV and CARDAAS give the same results. Comparing the two codes, one can conclude that CARDAAS and 3DVF predict quite well the distribution of the normal force coefficient. However, 3DVF is more time-consuming. Figure 6 compares the normal force coefficient’s distribution as a function of azimuthal angle for a 17-m wind turbine machine at TSR = 4.60 for a rotor rotation of 50.6 rpm. The distribution of the torque compares quite well with the experimental data. At the same time, it also gives the possibility to estimate the maximum and minimum torque encountered during the wind turbine rotation as a function of the azimuthal angle. Figure 7 compares the wind turbine’s theoretical performance with the experimental data for the Sandia 17-m turbine. The original CARDAA code does not include the variable interference factors used in CARDAAV code. As shown in this figure, CARDAA over predicts the power coefficient peak while CARDAAV shows a relatively good agreement with experimental data due to dynamic and secondary effects. Different dynamic stall models can be incorporated into the available aerodynamic codes. In Figure 8, the Gormont dynamic stall model and the improved Gormont model, along with the MIT dynamic stall models, have been used to predict the power generated by the wind turbine at different wind speeds.
Comparison of aerodynamic torque with experimental data at TSR = 4.60 and 50.6 rpm.
Performance comparison between theoretical and experimental data for the Sandia 17-m turbine.
Comparison of rotor power with different dynamic stall models at 50.6 rpm.
All in all, the models forecast well the power generated by the wind turbine, but the early version of the Gormont over predict that power. In fact, the improved Gormont model by Paraschivoiu [11] takes into account the fact that high-level turbulence delays the onset of the dynamic stall. Based on that, the improved Gormont dynamic stall model is used at low turbulence zone only, namely between an azimuthal angle of 135 degrees and 15 degrees; the rest of the azimuthal angle will ignore the dynamic stall. In the MIT model case, the dynamic-stall regime is characterized by some variation compared to the improved Gormont model. In Figure 9, we present the case of the QBlade code used for HAWT and VAWT. QBlade also uses the Blade Element Momentum (BEM) method and the DMS method to simulate HAWT and VAWT performance. Details on how to use QBlade can be found [31, 32, 33]. As an example, we generated the SG6043 airfoil pressure distribution generated using the XFOIL QBlade module. QBlade code can simulate the wake in the “Turbine Visualization” module, as shown in Figure 10. In Figure 11, we compare QBlade with CARDAAV code, including two dynamic stall models for the Sandia 34-m turbine, namely the indicial and improved Gormont models. The indicial model is used to simulate the effect of a dynamic stall at low tip-speed ratios; it is basically centered on the fact the dynamic stall is considered to be a superposition of several different effects that can be independently explored by using indicial functions [34]. As shown by Figure 11, all models predict quite well the power generated by the wind turbine but QBLADE slightly over predicts the power compared to CARDAAV. More validation of the QBLADE code in the case of VAWT can be found in [38].
Example of the SG6043 airfoil pressure distribution generated by QBlade.
Example of the wake simulation generated by QBlade.
Power distribution for the Sandia 34-m turbine using indicial and improved Gormont models at 34 rpm.
This book chapter emphasizes progress in the development of the aerodynamic codes for the prediction of HAWT and VAWT such as CARDAAV and Qbalde, with a focus on the BEMN and DMS methods for predicting aerodynamic and performance of wind turbines, including normal and tangential forces, torque, and the power generated by the wind turbine. The dynamic stall has been incorporated in this study to show the effects of this phenomenon on wind turbines’ performance. The codes have been successfully applied compared to available experimental data for the 17 m and 34 m wind turbine machines. The strength of the available codes lies in their simplicity, fast prediction, and ability to include secondary effects. More work is now needed to simulate wind turbine wake and predict the performance of wind turbine farms, which requires the understanding of the physics of the atmospheric wind flow, the structure and dynamics of large-scale machines, and the enhancement of energy capture, control, stability, optimization, and reliability.
The authors gratefully acknowledge the support of the College of Engineering at Effat University, Jeddah, the Kingdom of Saudi Arabia, and the J.- Armand Bombardier Chair at Polytechnique of Montreal, Canada.
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On September, 29th 2006 he has won a post PhD fellowship from the university of Bologna (from October 2006 to October 2008), at the competitive examination he was ranked first in the industrial engineering area. He extensively served as referee for several international journals. He is author/coauthor of more than 100 research papers. He has been involved in some projects supported by MURST and European Community. 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Here we consider the possibility that massless gravitons suffering slow redshift may be responsible for the properties of spiral galaxies attributed to dark matter. Particles such as gravitons will be extremely difficult to directly detect; the best we can envision is measuring this influence on stellar and galactic motions. Since the motions of stars and galaxies are non-relativistic, we can apply our idea to describe the expected large-scale motions using only Newtonian mechanics. Using our assumption about the importance of the graviton, we here describe the well-known Tully-Fisher relationship of spiral galaxies without resorting to hypothesizing exotic WIMPs or invoking modifications of Newtonian dynamics (MoND).",book:{id:"10954",title:"Dark Matter - Recent Observations and Theoretical Advances",coverURL:"https://cdn.intechopen.com/books/images_new/10954.jpg"},signatures:"Firmin Oliveira and Michael L. Smith"},{id:"79591",title:"Cosmology and Cosmic Rays Propagation in the Relativity with a Preferred Frame",slug:"cosmology-and-cosmic-rays-propagation-in-the-relativity-with-a-preferred-frame",totalDownloads:59,totalDimensionsCites:0,doi:"10.5772/intechopen.101032",abstract:"In this chapter, cosmological models and the processes accompanying the propagation of the cosmic rays on cosmological scales are considered based on particle dynamics, electrodynamics and general relativity (GR) developed from the basic concepts of the ‘relativity with a preferred frame’. The ‘relativity with a preferred frame’, designed to reconcile the relativity principle with the existence of the cosmological preferred frame, incorporates the preferred frame at the fundamental level of special relativity (SR) while retaining the fundamental space-time symmetry which, in the standard SR, manifests itself as Lorentz invariance. The cosmological models based on the modified GR of the ‘relativity with a preferred frame’ allow us to explain the SNIa observational data without introducing the dark energy and also fit other observational data, in particular, the BAO data. Applying the theory to the photo pion-production and pair-production processes, accompanying the propagation of the Ultra-High Energy Cosmic Rays (UHECR) and gamma rays through the universal diffuse background radiation, shows that the modified particle dynamics, electrodynamics and GR lead to measurable signatures in the observed cosmic rays spectra which can provide an interpretation of some puzzling features found in the observational data. Other possible observational consequences of the theory, such as the birefringence of light propagating in vacuo and dispersion, are discussed.",book:{id:"10954",title:"Dark Matter - Recent Observations and Theoretical Advances",coverURL:"https://cdn.intechopen.com/books/images_new/10954.jpg"},signatures:"Georgy I. Burde"},{id:"78811",title:"Black Holes as Possible Dark Matter",slug:"black-holes-as-possible-dark-matter",totalDownloads:102,totalDimensionsCites:0,doi:"10.5772/intechopen.99766",abstract:"Black holes and Dark matter are two fascinating things that are known very little. They may have non gravitational interactions, but those are definitely extremely feeble in comparison to their gravitational interactions. Nowadays some people think that one may contain the other. In this chapter we will see that some black holes may contain the dark matter. These black holes decay under Hawking radiation, but do not vanish completely. They produce stable end states due to both quantum gravitational effects and thermodynamic reasons. These end states are the replicas of what we call dark matter. We will develop the complete theory for decay of such black holes, starting from some scheme independent assumptions for the quantum mechanical nature of the black holes. We will then consider explicit examples of some black holes to show that they indeed produce replicas of dark matter at their end states. Thus this chapter is going to be a manuscript for theoretical development of black hole decay from a quantum mechanical perspective and its consequences for producing replicas of dark matter.",book:{id:"10954",title:"Dark Matter - Recent Observations and Theoretical Advances",coverURL:"https://cdn.intechopen.com/books/images_new/10954.jpg"},signatures:"Aloke Kumar Sinha"},{id:"78389",title:"Non-Keplerian Orbits in Dark Matter",slug:"non-keplerian-orbits-in-dark-matter",totalDownloads:92,totalDimensionsCites:0,doi:"10.5772/intechopen.99243",abstract:"This paper is concerned with the mathematical description of orbits that do not have a constant central gravitating mass. Instead, the attracting mass is a diffuse condensate, a situation which classical orbital dynamics has never encountered before. The famous Coma Cluster of Galaxies is embedded in Dark Matter. Condensed Neutrino Objects (CNO), which are stable assemblages of neutrinos and anti-neutrinos, are candidates for the Dark Matter. A CNO solution has been attained previously for the Coma Cluster, which allows mathematical modeling of galaxy orbital mechanics within Dark Matter, first reported here. For non-zero eccentricity galaxy orbits, each point along the trajectory sees a different gravitating central mass, akin to satellite orbits inside Earth. Mathematically, the galaxy orbits are non-Keplerian, spirographs.",book:{id:"10954",title:"Dark Matter - Recent Observations and Theoretical Advances",coverURL:"https://cdn.intechopen.com/books/images_new/10954.jpg"},signatures:"Peter D. Morley"},{id:"77754",title:"The Most Probable Cosmic Scale Factor Consistent with the Cosmological Principle, General Relativity and the SMPP",slug:"the-most-probable-cosmic-scale-factor-consistent-with-the-cosmological-principle-general-relativity-",totalDownloads:201,totalDimensionsCites:1,doi:"10.5772/intechopen.99325",abstract:"Current literature on the evolution of the cosmic scale factor is dominated by models using a dark sector, these all involve making many conjectures beyond the basic assumption that the Cosmological Principle selects a space–time metric of the Friedmann–Lemaître–Robertson–Walker type through which ordinary Standard Model of Particle Physics matter moves according to General Relativity. In this chapter a different model is made using the same basic assumptions but without making extra conjectures, it depends on following the idea introduced by Boltzmann that when physically meaningful concepts fluctuate the value which will be observed is the one which has the highest probability. This change removes the mathematically incorrect procedure of averaging the matter density before solving Einstein’s Equation, the procedure which causes the introduction of many of the conjectures. In the non-uniform era the changes are that the evolution of the scale factor is influenced by the formation of structure and removes the conjecture of having to use two inconsistent probability distributions for matter through space, one to calculate the scale factor and one to represent structure. The new model is consistent from the earliest times through to the present epoch. This new model is open and matches SNe 1a redshift data, an observation which makes it a viable candidate and implies that it should be fully investigated.",book:{id:"10954",title:"Dark Matter - Recent Observations and Theoretical Advances",coverURL:"https://cdn.intechopen.com/books/images_new/10954.jpg"},signatures:"Arthur N. James"},{id:"76451",title:"The Case for Cold Hydrogen Dark Matter",slug:"the-case-for-cold-hydrogen-dark-matter",totalDownloads:201,totalDimensionsCites:0,doi:"10.5772/intechopen.97557",abstract:"The novel ‘Cold Hydrogen Dark Matter’ (CHDM) theory is summarized in this chapter. Special attention is paid to the fact that current technology prevents us from directly observing extremely cold ground state atomic hydrogen when it is of sufficiently low density in deep space locations. A number of very recent observations in support of this theory are summarized, including cosmic dawn constraints on dark matter. The importance of the Wouthuysen-Field effect as a probable mechanism for CMB decoupling of hydrogen at cosmic dawn is also stressed. This mechanism does not require a non-baryonic dark matter intermediary. Several predictions for this theory are made for the coming decade of observations and simulations.",book:{id:"10954",title:"Dark Matter - Recent Observations and Theoretical Advances",coverURL:"https://cdn.intechopen.com/books/images_new/10954.jpg"},signatures:"Eugene Terry Tatum"}],onlineFirstChaptersTotal:6},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:8,limit:8,total:0},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:87,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:98,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:27,numberOfPublishedChapters:287,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:9,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:139,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:129,numberOfOpenTopics:0,numberOfUpcomingTopics:2,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!1},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:107,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:10,numberOfPublishedChapters:103,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:12,numberOfOpenTopics:2,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:0,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!1},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:0,numberOfPublishedChapters:10,numberOfOpenTopics:4,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. 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The area covers many techniques that offer solutions to emerging problems in robotics and enterprise-level software systems. Collaborative intelligence is highly and effectively achieved with multi-agent systems. Areas of application include swarms of robots, flocks of UAVs, collaborative software management. Given the level of technological enhancements, the popularity of machine learning in use has opened a new chapter in multi-agent studies alongside the practical challenges and long-lasting collaboration issues in the field. It has increased the urgency and the need for further studies in this field. We welcome chapters presenting research on the many applications of multi-agent studies including, but not limited to, the following key areas: machine learning for multi-agent systems; modeling swarms robots and flocks of UAVs with multi-agent systems; decision science and multi-agent systems; software engineering for and with multi-agent systems; tools and technologies of multi-agent systems.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/27.jpg",hasOnlineFirst:!1,hasPublishedBooks:!1,annualVolume:11423,editor:{id:"148497",title:"Dr.",name:"Mehmet",middleName:"Emin",surname:"Aydin",slug:"mehmet-aydin",fullName:"Mehmet Aydin",profilePictureURL:"https://mts.intechopen.com/storage/users/148497/images/system/148497.jpg",biography:"Dr. Mehmet Emin Aydin is a Senior Lecturer with the Department of Computer Science and Creative Technology, the University of the West of England, Bristol, UK. 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a prestigious publisher allows for the possibility to collaborate with more research groups interested in animal nutrition, leading to the development of new feeding strategies and food valuation while being more sustainable with the environment, allowing more readers to learn about the subject.",author:{id:"175967",name:"Manuel",surname:"Gonzalez Ronquillo",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/175967/images/system/175967.png",slug:"manuel-gonzalez-ronquillo",institution:{id:"6221",name:"Universidad Autónoma del Estado de México",country:{id:null,name:"Mexico"}}}},{id:"18",text:"It was great publishing with IntechOpen, the process was straightforward and I had support all along.",author:{id:"71579",name:"Berend",surname:"Olivier",institutionString:"Utrecht University",profilePictureURL:"https://mts.intechopen.com/storage/users/71579/images/system/71579.png",slug:"berend-olivier",institution:{id:"253",name:"Utrecht 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Fungal infectious illness prevalence and prognosis are determined by the exposure between fungi and host, host immunological state, fungal virulence, and early and accurate diagnosis and treatment. \r\nPatients with both congenital and acquired immunodeficiency are more likely to be infected with opportunistic mycosis. Fungal infectious disease outbreaks are common during the post- disaster rebuilding era, which is characterised by high population density, migration, and poor health and medical conditions.\r\nSystemic or local fungal infection is mainly associated with the fungi directly inhaled or inoculated in the environment during the disaster. The most common fungal infection pathways are human to human (anthropophilic), animal to human (zoophilic), and environment to human (soilophile). Diseases are common as a result of widespread exposure to pathogenic fungus dispersed into the environment. \r\nFungi that are both common and emerging are intertwined. In Southeast Asia, for example, Talaromyces marneffei is an important pathogenic thermally dimorphic fungus that causes systemic mycosis. Widespread fungal infections with complicated and variable clinical manifestations, such as Candida auris infection resistant to several antifungal medicines, Covid-19 associated with Trichoderma, and terbinafine resistant dermatophytosis in India, are among the most serious disorders. \r\nInappropriate local or systemic use of glucocorticoids, as well as their immunosuppressive effects, may lead to changes in fungal infection spectrum and clinical characteristics. Hematogenous candidiasis is a worrisome issue that affects people all over the world, particularly ICU patients. CARD9 deficiency and fungal infection have been major issues in recent years. Invasive aspergillosis is associated with a significant death rate. Special attention should be given to endemic fungal infections, identification of important clinical fungal infections advanced in yeasts, filamentous fungal infections, skin mycobiome and fungal genomes, and immunity to fungal infections.\r\nIn addition, endemic fungal diseases or uncommon fungal infections caused by Mucor irregularis, dermatophytosis, Malassezia, cryptococcosis, chromoblastomycosis, coccidiosis, blastomycosis, histoplasmosis, sporotrichosis, and other fungi, should be monitored. \r\nThis topic includes the research progress on the etiology and pathogenesis of fungal infections, new methods of isolation and identification, rapid detection, drug sensitivity testing, new antifungal drugs, schemes and case series reports. It will provide significant opportunities and support for scientists, clinical doctors, mycologists, antifungal drug researchers, public health practitioners, and epidemiologists from all over the world to share new research, ideas and solutions to promote the development and progress of medical mycology.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/4.jpg",keywords:"Emerging Fungal Pathogens, Invasive Infections, Epidemiology, Cell Membrane, Fungal Virulence, Diagnosis, Treatment"},{id:"5",title:"Parasitic Infectious Diseases",scope:"Parasitic diseases have evolved alongside their human hosts. In many cases, these diseases have adapted so well that they have developed efficient resilience methods in the human host and can live in the host for years. Others, particularly some blood parasites, can cause very acute diseases and are responsible for millions of deaths yearly. Many parasitic diseases are classified as neglected tropical diseases because they have received minimal funding over recent years and, in many cases, are under-reported despite the critical role they play in morbidity and mortality among human and animal hosts. The current topic, Parasitic Infectious Diseases, in the Infectious Diseases Series aims to publish studies on the systematics, epidemiology, molecular biology, genomics, pathogenesis, genetics, and clinical significance of parasitic diseases from blood borne to intestinal parasites as well as zoonotic parasites. We hope to cover all aspects of parasitic diseases to provide current and relevant research data on these very important diseases. In the current atmosphere of the Coronavirus pandemic, communities around the world, particularly those in different underdeveloped areas, are faced with the growing challenges of the high burden of parasitic diseases. At the same time, they are faced with the Covid-19 pandemic leading to what some authors have called potential syndemics that might worsen the outcome of such infections. Therefore, it is important to conduct studies that examine parasitic infections in the context of the coronavirus pandemic for the benefit of all communities to help foster more informed decisions for the betterment of human and animal health.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/5.jpg",keywords:"Blood Borne Parasites, Intestinal Parasites, Protozoa, Helminths, Arthropods, Water Born Parasites, Epidemiology, Molecular Biology, Systematics, Genomics, Proteomics, Ecology"},{id:"6",title:"Viral Infectious Diseases",scope:"The Viral Infectious Diseases Book Series aims to provide a comprehensive overview of recent research trends and discoveries in various viral infectious diseases emerging around the globe. The emergence of any viral disease is hard to anticipate, which often contributes to death. A viral disease can be defined as an infectious disease that has recently appeared within a population or exists in nature with the rapid expansion of incident or geographic range. This series will focus on various crucial factors related to emerging viral infectious diseases, including epidemiology, pathogenesis, host immune response, clinical manifestations, diagnosis, treatment, and clinical recommendations for managing viral infectious diseases, highlighting the recent issues with future directions for effective therapeutic strategies.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/6.jpg",keywords:"Novel Viruses, Virus Transmission, Virus Evolution, Molecular Virology, Control and Prevention, Virus-host Interaction"}],annualVolumeBook:{},thematicCollection:[],selectedSeries:null,selectedSubseries:null},seriesLanding:{item:{id:"11",title:"Biochemistry",doi:"10.5772/intechopen.72877",issn:"2632-0983",scope:"Biochemistry, the study of chemical transformations occurring within living organisms, impacts all areas of life sciences, from molecular crystallography and genetics to ecology, medicine, and population biology. Biochemistry examines macromolecules - proteins, nucleic acids, carbohydrates, and lipids – and their building blocks, structures, functions, and interactions. Much of biochemistry is devoted to enzymes, proteins that catalyze chemical reactions, enzyme structures, mechanisms of action and their roles within cells. Biochemistry also studies small signaling molecules, coenzymes, inhibitors, vitamins, and hormones, which play roles in life processes. Biochemical experimentation, besides coopting classical chemistry methods, e.g., chromatography, adopted new techniques, e.g., X-ray diffraction, electron microscopy, NMR, radioisotopes, and developed sophisticated microbial genetic tools, e.g., auxotroph mutants and their revertants, fermentation, etc. More recently, biochemistry embraced the ‘big data’ omics systems. Initial biochemical studies have been exclusively analytic: dissecting, purifying, and examining individual components of a biological system; in the apt words of Efraim Racker (1913 –1991), “Don’t waste clean thinking on dirty enzymes.” Today, however, biochemistry is becoming more agglomerative and comprehensive, setting out to integrate and describe entirely particular biological systems. The ‘big data’ metabolomics can define the complement of small molecules, e.g., in a soil or biofilm sample; proteomics can distinguish all the comprising proteins, e.g., serum; metagenomics can identify all the genes in a complex environment, e.g., the bovine rumen. This Biochemistry Series will address the current research on biomolecules and the emerging trends with great promise.",coverUrl:"https://cdn.intechopen.com/series/covers/11.jpg",latestPublicationDate:"May 18th, 2022",hasOnlineFirst:!0,numberOfOpenTopics:4,numberOfPublishedChapters:287,numberOfPublishedBooks:27,editor:{id:"31610",title:"Dr.",name:"Miroslav",middleName:null,surname:"Blumenberg",fullName:"Miroslav Blumenberg",profilePictureURL:"https://mts.intechopen.com/storage/users/31610/images/system/31610.jpg",biography:"Miroslav Blumenberg, Ph.D., was born in Subotica and received his BSc in Belgrade, Yugoslavia. He completed his Ph.D. at MIT in Organic Chemistry; he followed up his Ph.D. with two postdoctoral study periods at Stanford University. Since 1983, he has been a faculty member of the RO Perelman Department of Dermatology, NYU School of Medicine, where he is codirector of a training grant in cutaneous biology. Dr. Blumenberg’s research is focused on the epidermis, expression of keratin genes, transcription profiling, keratinocyte differentiation, inflammatory diseases and cancers, and most recently the effects of the microbiome on the skin. He has published more than 100 peer-reviewed research articles and graduated numerous Ph.D. and postdoctoral students.",institutionString:null,institution:{name:"New York University Langone Medical Center",institutionURL:null,country:{name:"United States of America"}}},subseries:[{id:"14",title:"Cell and Molecular Biology",keywords:"Omics (Transcriptomics; Proteomics; Metabolomics), Molecular Biology, Cell Biology, Signal Transduction and Regulation, Cell Growth and Differentiation, Apoptosis, Necroptosis, Ferroptosis, Autophagy, Cell Cycle, Macromolecules and Complexes, Gene Expression",scope:"The Cell and Molecular Biology topic within the IntechOpen Biochemistry Series aims to rapidly publish contributions on all aspects of cell and molecular biology, including aspects related to biochemical and genetic research (not only in humans but all living beings). We encourage the submission of manuscripts that provide novel and mechanistic insights that report significant advances in the fields. Topics include, but are not limited to: Advanced techniques of cellular and molecular biology (Molecular methodologies, imaging techniques, and bioinformatics); Biological activities at the molecular level; Biological processes of cell functions, cell division, senescence, maintenance, and cell death; Biomolecules interactions; Cancer; Cell biology; Chemical biology; Computational biology; Cytochemistry; Developmental biology; Disease mechanisms and therapeutics; DNA, and RNA metabolism; Gene functions, genetics, and genomics; Genetics; Immunology; Medical microbiology; Molecular biology; Molecular genetics; Molecular processes of cell and organelle dynamics; Neuroscience; Protein biosynthesis, degradation, and functions; Regulation of molecular interactions in a cell; Signalling networks and system biology; Structural biology; Virology and microbiology.",annualVolume:11410,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/14.jpg",editor:{id:"165627",title:"Dr.",name:"Rosa María",middleName:null,surname:"Martínez-Espinosa",fullName:"Rosa María Martínez-Espinosa",profilePictureURL:"https://mts.intechopen.com/storage/users/165627/images/system/165627.jpeg",institutionString:null,institution:{name:"University of Alicante",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"79367",title:"Dr.",name:"Ana Isabel",middleName:null,surname:"Flores",fullName:"Ana Isabel Flores",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRpIOQA0/Profile_Picture_1632418099564",institutionString:null,institution:{name:"Hospital Universitario 12 De Octubre",institutionURL:null,country:{name:"Spain"}}},{id:"328234",title:"Ph.D.",name:"Christian",middleName:null,surname:"Palavecino",fullName:"Christian Palavecino",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000030DhEhQAK/Profile_Picture_1628835318625",institutionString:null,institution:{name:"Central University of Chile",institutionURL:null,country:{name:"Chile"}}},{id:"186585",title:"Dr.",name:"Francisco Javier",middleName:null,surname:"Martin-Romero",fullName:"Francisco Javier Martin-Romero",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSB3HQAW/Profile_Picture_1631258137641",institutionString:null,institution:{name:"University of Extremadura",institutionURL:null,country:{name:"Spain"}}}]},{id:"15",title:"Chemical Biology",keywords:"Phenolic Compounds, Essential Oils, Modification of Biomolecules, Glycobiology, Combinatorial Chemistry, Therapeutic peptides, Enzyme Inhibitors",scope:"Chemical biology spans the fields of chemistry and biology involving the application of biological and chemical molecules and techniques. In recent years, the application of chemistry to biological molecules has gained significant interest in medicinal and pharmacological studies. This topic will be devoted to understanding the interplay between biomolecules and chemical compounds, their structure and function, and their potential applications in related fields. Being a part of the biochemistry discipline, the ideas and concepts that have emerged from Chemical Biology have affected other related areas. This topic will closely deal with all emerging trends in this discipline.",annualVolume:11411,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/15.jpg",editor:{id:"441442",title:"Dr.",name:"Şükrü",middleName:null,surname:"Beydemir",fullName:"Şükrü Beydemir",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003GsUoIQAV/Profile_Picture_1634557147521",institutionString:null,institution:{name:"Anadolu University",institutionURL:null,country:{name:"Turkey"}}},editorTwo:{id:"13652",title:"Prof.",name:"Deniz",middleName:null,surname:"Ekinci",fullName:"Deniz Ekinci",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYLT1QAO/Profile_Picture_1634557223079",institutionString:null,institution:{name:"Ondokuz Mayıs University",institutionURL:null,country:{name:"Turkey"}}},editorThree:null,editorialBoard:[{id:"241413",title:"Dr.",name:"Azhar",middleName:null,surname:"Rasul",fullName:"Azhar Rasul",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRT1oQAG/Profile_Picture_1635251978933",institutionString:null,institution:{name:"Government College University, Faisalabad",institutionURL:null,country:{name:"Pakistan"}}},{id:"178316",title:"Ph.D.",name:"Sergey",middleName:null,surname:"Sedykh",fullName:"Sergey Sedykh",profilePictureURL:"https://mts.intechopen.com/storage/users/178316/images/system/178316.jfif",institutionString:null,institution:{name:"Novosibirsk State University",institutionURL:null,country:{name:"Russia"}}}]},{id:"17",title:"Metabolism",keywords:"Biomolecules Metabolism, Energy Metabolism, Metabolic Pathways, Key Metabolic Enzymes, Metabolic Adaptation",scope:"Metabolism is frequently defined in biochemistry textbooks as the overall process that allows living systems to acquire and use the free energy they need for their vital functions or the chemical processes that occur within a living organism to maintain life. Behind these definitions are hidden all the aspects of normal and pathological functioning of all processes that the topic ‘Metabolism’ will cover within the Biochemistry Series. Thus all studies on metabolism will be considered for publication.",annualVolume:11413,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/17.jpg",editor:{id:"138626",title:"Dr.",name:"Yannis",middleName:null,surname:"Karamanos",fullName:"Yannis Karamanos",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002g6Jv2QAE/Profile_Picture_1629356660984",institutionString:null,institution:{name:"Artois University",institutionURL:null,country:{name:"France"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"243049",title:"Dr.",name:"Anca",middleName:null,surname:"Pantea Stoian",fullName:"Anca Pantea Stoian",profilePictureURL:"https://mts.intechopen.com/storage/users/243049/images/system/243049.jpg",institutionString:null,institution:{name:"Carol Davila University of Medicine and Pharmacy",institutionURL:null,country:{name:"Romania"}}},{id:"203824",title:"Dr.",name:"Attilio",middleName:null,surname:"Rigotti",fullName:"Attilio Rigotti",profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institutionString:null,institution:{name:"Pontifical Catholic University of Chile",institutionURL:null,country:{name:"Chile"}}},{id:"300470",title:"Dr.",name:"Yanfei (Jacob)",middleName:null,surname:"Qi",fullName:"Yanfei (Jacob) Qi",profilePictureURL:"https://mts.intechopen.com/storage/users/300470/images/system/300470.jpg",institutionString:null,institution:{name:"Centenary Institute of Cancer Medicine and Cell Biology",institutionURL:null,country:{name:"Australia"}}}]},{id:"18",title:"Proteomics",keywords:"Mono- and Two-Dimensional Gel Electrophoresis (1-and 2-DE), Liquid Chromatography (LC), Mass Spectrometry/Tandem Mass Spectrometry (MS; MS/MS), Proteins",scope:"With the recognition that the human genome cannot provide answers to the etiology of a disorder, changes in the proteins expressed by a genome became a focus in research. Thus proteomics, an area of research that detects all protein forms expressed in an organism, including splice isoforms and post-translational modifications, is more suitable than genomics for a comprehensive understanding of the biochemical processes that govern life. The most common proteomics applications are currently in the clinical field for the identification, in a variety of biological matrices, of biomarkers for diagnosis and therapeutic intervention of disorders. From the comparison of proteomic profiles of control and disease or different physiological states, which may emerge, changes in protein expression can provide new insights into the roles played by some proteins in human pathologies. Understanding how proteins function and interact with each other is another goal of proteomics that makes this approach even more intriguing. Specialized technology and expertise are required to assess the proteome of any biological sample. Currently, proteomics relies mainly on mass spectrometry (MS) combined with electrophoretic (1 or 2-DE-MS) and/or chromatographic techniques (LC-MS/MS). MS is an excellent tool that has gained popularity in proteomics because of its ability to gather a complex body of information such as cataloging protein expression, identifying protein modification sites, and defining protein interactions. The Proteomics topic aims to attract contributions on all aspects of MS-based proteomics that, by pushing the boundaries of MS capabilities, may address biological problems that have not been resolved yet.",annualVolume:11414,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/18.jpg",editor:{id:"200689",title:"Prof.",name:"Paolo",middleName:null,surname:"Iadarola",fullName:"Paolo Iadarola",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSCl8QAG/Profile_Picture_1623568118342",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorTwo:{id:"201414",title:"Dr.",name:"Simona",middleName:null,surname:"Viglio",fullName:"Simona Viglio",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRKDHQA4/Profile_Picture_1630402531487",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorThree:null,editorialBoard:[{id:"72288",title:"Dr.",name:"Arli Aditya",middleName:null,surname:"Parikesit",fullName:"Arli Aditya Parikesit",profilePictureURL:"https://mts.intechopen.com/storage/users/72288/images/system/72288.jpg",institutionString:null,institution:{name:"Indonesia International Institute for Life Sciences",institutionURL:null,country:{name:"Indonesia"}}},{id:"40928",title:"Dr.",name:"Cesar",middleName:null,surname:"Lopez-Camarillo",fullName:"Cesar Lopez-Camarillo",profilePictureURL:"https://mts.intechopen.com/storage/users/40928/images/3884_n.png",institutionString:null,institution:{name:"Universidad Autónoma de la Ciudad de México",institutionURL:null,country:{name:"Mexico"}}},{id:"81926",title:"Dr.",name:"Shymaa",middleName:null,surname:"Enany",fullName:"Shymaa Enany",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRqB9QAK/Profile_Picture_1626163237970",institutionString:null,institution:{name:"Suez Canal University",institutionURL:null,country:{name:"Egypt"}}}]}]}},libraryRecommendation:{success:null,errors:{},institutions:[]},route:{name:"chapter.detail",path:"/chapters/75643",hash:"",query:{},params:{id:"75643"},fullPath:"/chapters/75643",meta:{},from:{name:null,path:"/",hash:"",query:{},params:{},fullPath:"/",meta:{}}}},function(){var e;(e=document.currentScript||document.scripts[document.scripts.length-1]).parentNode.removeChild(e)}()